Introduction
Liver cancer ranks as the second leading cause of cancer-related deaths globally, with a continually increasing incidence rate. Projections indicate that by 2025, over 1 million individuals will be diagnosed with liver cancer [
1]. Hepatocellular carcinoma (HCC) represents the primary type of liver cancer. Surgical resection serves as the principal treatment for early-stage liver cancer; however, when lymph node or distant metastasis occurs, the survival rate plummets dramatically [
2]. Although immune checkpoint inhibitors demonstrate some efficacy in treating liver cancer patients, the response rate remains unsatisfactory [
3]. Consequently, identifying critical targets that influence drug tolerance and distant metastasis in liver cancer holds significant importance.
Protein-
l-isoaspartate (
d-aspartate)
O-methyltransferase (PCMT1) functions as a protein repair enzyme. Historically, research has predominantly concentrated on its role in protein repair and metabolism, which can affect neural repair [
4]. Recent studies have revealed a substantial function for PCMT1 in tumor development and progression [
5]. Additionally, it has been discovered that PCMT1 can restructure myocardin and microtubule cells, thus promoting glioblastoma migration and invasion [
6]. Emerging research indicates that PCMT1 expression influences immune infiltration in breast cancer, and related studies have corroborated PCMT1 as a crucial driver of ovarian cancer metastasis [
7,
8]. Despite investigations into PCMT1's role in various tumors, its significance in liver cancer remains elusive. Therefore, we utilized publicly available databases and integrated bioinformatics methods to conduct a preliminary investigation into the relationship between PCMT1 expression and liver cancer patient prognosis. Moreover, we explored its potential mechanisms in LIHC through RNA sequencing and pertinent experiments.
Methods
Data acquisition
In this study, we downloaded data from the TCGA website for 33 types of cancers, obtaining a total of 11,116 samples, including gene expression information and clinical characteristics of tumor and non-tumor samples. We further analyzed the relevant data specific to liver cancer. The genetic symbols were obtained directly from the database, and gene expression data were normalized using log2(TPM + 0.001). We extracted survival and clinical phenotype data for liver cancer patients and excluded samples without prognostic information, resulting in 374 tumor samples and 50 samples of normal adjacent tissue. Our primary focus is the correlation between PCMT1 expression and prognosis of liver cancer patients. We utilized R software to analyze the relationship between PCMT1 expression and immune cell infiltration levels in liver cancer.
Functional enrichment analysis of differential expression genes (DEGs)
Utilizing R software, we initially identified differentially expressed genes (DEGs) between high and low PCMT1 expression groups [
9]. We used a heatmap to visually analyze the Spearman correlation between the top 50 DEGs and PCMT1, and further conducted functional enrichment analysis, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Finally, we performed GSEA analysis based on the "Molecular Signatures Database" c2.cp.kegg.v7.1.symbols to assess possible underlying mechanisms [
10]. We selected a random sample size of 100, and only results with
P < 0.05 were considered to be statistically significant.
PCMT1 and tumor immunity
We used the ESTIMATE algorithm to analyze the relationship between immune cell infiltration and PCMT1 expression in tumors [
11,
12]. Additionally, we used the "corrplot" and "ggpubr" packages in R to analyze the correlation between PCMT1 levels and selected immune-related gene markers. TCIA algorithm was used to predict the impact of PCMT1 expression on the response to immunotherapy in LIHC patients.
Analysis of TMB (tumor mutational burden) and tumor gene mutations.
We obtained somatic mutation data for all LIHC patients from TCGA, calculated the tumor mutation burden (TMB) score using R software, and analyzed the correlation between TMB and PCMT1 expression levels [
11,
13]. In addition, we further analyzed the differences in gene mutations between the high and low PCMT1 expression groups of LIHC samples.
Drug sensitivity prediction
We employed the "prophetic" R package to compute the IC50 of chemotherapy drugs [
14]. This method is primarily utilized to predict the effectiveness of a substance in inhibiting a specific biological or biochemical process. Using this approach, we can assess the potential correlation between PCMT1 expression and drug sensitivity, thereby screening potential candidate drugs for LIHC patients.
Patients tissue sample acquisition
The tumor tissue and corresponding adjacent tissue of liver cancer patients were obtained from the Third Xiangya Hospital. The tumor tissue was pathologically diagnosed as LIHC.
Cell culture
We procured hepatic carcinoma cell lines (HepG2 and Hep1-6) from the Shanghai Cell Bank, and we cultured them in DMEM high glucose medium supplemented with 10% fetal bovine serum and 1% penicillin–streptomycin. The cells were maintained in a culture environment with a stable temperature of 37 °C and a CO2 concentration of 5%. To obtain LIHC cells with PCMT1 knockdown, shRNA targeting PCMT1 was transfected when the cell density achieved 50–70% by Lipofectamine3000, cells were screened for antibiotics to enrich cells with integrated shRNA structures. The expression level of target genes was evaluated by western blotting to determine the knockout efficiency of stable cell lines.
Cell counting kit-8 (CCK-8) assay
We seeded normal and PCMT1 knockdown cells in 96-well plates at a density of 2 × 103 cells per well. After adding CCK8 reagent, the cells were incubated for 1 h and the cell proliferation was measured at 450 nm.
Transwell assay
The corresponding cells were seeded at a density of 2.0 × 105 cells per well and cultured for an additional 48 h. The migration ability of the hepatic carcinoma cells was determined using the Transwell assay.
Apoptosis assay
The Apoptosis Detection Kit (catalog #556547, BD) was used to investigate the impact of PCMT1 on cell apoptosis. The experimental procedures were performed according to the instructions provided with the kit, and flow cytometry was used to detect the results.
Establishment of mouse tumor model
The hep1-6 cells are washed with PBS to obtain a suspension of 1 × 107 cells/ml. Adult C57BL/6 male mice are used for the tumor model. Mice are acclimatized for a week before the experiment, and their health is monitored daily. The mice are anesthetized with isoflurane, and the Hep1-6 cell suspension (100 µL) is injected subcutaneously into the right flank of each mouse. The mouse tumor size was measured every 3 days using a vernier caliper. Once the tumor reached an appropriate size, the mouse was euthanized, and the tumor was collected for further analysis, such as histological examination, immunohistochemistry, immunofluorescence and gene expression analysis.
Detection of immune cell infiltration
The mouse tumor tissue is dissected and mechanically dissociated with scissors and forceps. The tumor tissue is then enzymatically digested using a cocktail of collagenase, hyaluronidase, and DNase. The digested tumor tissue is filtered through a 70-µm cell strainer to obtain a single-cell suspension, stained with corresponding T cell antibodies, and analyzed by flow cytometry. The infiltration and polarization of macrophages in the tumor were evaluated by immunofluorescence staining.
Statistical method
In our study, we aimed to investigate the association between PCMT1 expression and prognosis in liver cancer patients by analyzing the clinical indicators of OS and PFS. We used the Wilcoxon log-rank test to compare the sum of gene expression z-scores between cancerous and adjacent normal tissues, and the Kruskal–Wallis test to assess the differences in PCMT1 expression among different tumor stages. The survival analyses were conducted using KM curves, the log-rank test, and Cox proportional hazards regression models. Additionally, we performed Spearman’s test to evaluate the correlation between PCMT1 expression and clinical parameters. All statistical analyses were carried out using the R programming language (version 4.1.0; R Foundation), and a two-sided P-value less than 0.05 was considered statistically significant.
Discussion
In this study, we discovered that PCMT1 was overexpressed in hepatocellular carcinoma. Additionally, we investigated the relationship between PCMT1 mRNA expression and various clinical variables such as tumor status, lymph node status, distant metastasis, and pathological staging. The results indicated that high PCMT1 expression was associated with poor prognosis and was an independent prognostic factor for survival. Through gene expression profiling analysis and in vitro and in vivo experiments, we further explored the potential mechanisms of PCMT1 in the progression of liver cancer.
We first analyzed the differentially expressed genes between PCMT1 high and low expression patients. KEGG and GO analysis revealed that these genes were mainly enriched in immune-related pathways and protein digestion and absorption, and could also affect cell cycle. Further GSEA analysis revealed that PCMT1 affects the synthesis of primary bile acids. Previous studies have demonstrated that primary bile acids can recruit NKT cells to suppress liver cancer [
15]. Based on our analysis, PCMT1 is likely to impact the proliferation of liver cancer cells as well as the formation of the tumor microenvironment. We then analyzed the differences in immune microenvironment between the two groups. Our results showed that there were significant differences in the proportion of immune cells between PCMT1 high and low expression groups, and the infiltration level of different cells was significantly correlated with PCMT1 copy number. CD4+memory T cells infiltrated more in PCMT1 high expression patients while NK cells infiltrated less. NK cells and CD4+T cells have been proven to play important roles in liver cancer and are associated with various treatment outcomes [
16‐
20]. Therefore, PCMT1 expression is likely to affect the tumor microenvironment. We further analyzed and found that PCMT1 expression was positively correlated with immune checkpoint expression, which could be one of the reasons for the poor survival rate in PCMT1 high expression patients. PCMT1 expression was not related to tumor mutation burden, but immunotherapy data analysis showed that the immunotherapy effective rate might be lower in PCMT1 high expression patients. Therefore, based on our results, PCMT1 is likely to inhibit tumor immunity and promote tumor progression. In addition to immunotherapy, TACE therapy is also an important treatment for liver cancer [
21‐
23]. Our analysis of the database results revealed that the expression of PCMT1 was significantly lower in TACE-responsive patients compared to TACE non-responsive patients. Therefore, PCMT1 can also serve as a target for predicting the therapeutic effect and can aid in providing more accurate treatment for patients.
In order to further investigate the role of PCMT1 in liver cancer, we first analyzed the expression of PCMT1 in tumor tissue and adjacent tissue of liver cancer patients. The results showed that PCMT1 expression was significantly higher in liver cancer tissue than in adjacent tissue. Then, we established a stable cell line with low expression of PCMT1 through shRNA, in order to further study the role of PCMT1 in liver cancer cell lines. Through CCK8 and Transwell experiments, we found that knocking down PCMT1 could significantly inhibit the growth and migration of liver cancer cells. Further flow cytometry results showed a significant increase in apoptosis of cells after PCMT1 knockdown. PCMT1 may affect cell apoptosis through various mechanisms. Some studies suggest that PCMT1 can prevent cell apoptosis by affecting intracellular ROS levels and caspase-3/9 activity [
24]. Additionally, PCMT1 can also inhibit cell apoptosis induced by overexpression of Bax [
25]. Furthermore, after subarachnoid hemorrhage, MST1 is activated and promotes neuronal apoptosis, which can be significantly inhibited by PCMT1 [
26]. Moreover, there is evidence that downregulation of PCMT1 expression after DNA damage induced by various factors can significantly increase cell apoptosis [
27]. The mechanism of radiotherapy and some anti-tumor drugs involves the activation of reactive oxygen species or DNA damage [
28], thus PCMT1 is likely to be associated with radiotherapy resistance and drug resistance.
To explore the possible mechanisms of PCMT1 in liver cancer progression, we conducted RNA transcriptome sequencing and analyzed the differentially expressed genes between the two groups with or without PCMT1 knockdown. The results showed that PCMT1 may affect cell apoptosis and the PI3K–Akt pathway. The PI3K–Akt pathway is widely studied in tumors, and its activation can promote tumor proliferation, invasion, and metastasis, and is also related to tumor treatment resistance [
29‐
32]. To validate the sequencing results, we conducted further experiments and found that PCMT1 knockdown can promote the high expression of apoptosis-related proteins, and reduce the phosphorylation of PI3K and Akt, as well as inhibit EMT. Therefore, our results suggest that PCMT1 may be a crucial molecule in liver cancer progression.
Many studies have demonstrated that tumor cells can influence tumor progression by influencing tumor immune microenvironment [
33,
34]. In order to investigate the effects of PCMT1 on tumor growth and the tumor immune microenvironment, we further studied the role of PCMT1 in vivo by establishing a mouse model of liver cancer, we found that the tumor volume grew more slowly, and the apoptotic staining and caspase-3 expression were significantly higher in the tumor area in the knockdown group, suggesting that knockdown PCMT1 may promote the necrosis and apoptosis of tumor tissue. Related studies have shown that PCMT1 may exist in exocrine bodies and vesicles [
35,
36], it may have an effect on other cells in the tumor area. Therefore, we further tested the infiltration of CD4+ and CD8+T cells in the tumor area, and found that knockdown of PCMT1 significantly increased the infiltration of CD8+T cells, Activation of CD8+T cells is often considered a key factor in cancer immunotherapy [
37], although we did not observe significant changes in CD4+T cells, further subgroup analysis, such as whether there are changes in Treg cells, is also worth further investigation. Besides T cells, relevant literature also showed that macrophages also played an important role in tumor treatment [
38‐
40]. Therefore, we further evaluated the infiltration of M1 and M2 types of macrophages in the tumor area, and the results showed that CD86 expression was significantly increased and CD206 expression was decreased in the tumor area after PCMT1 knockdown, which may indicate that PCMT1 affects the polarization of macrophages in the tumor area, these evidences all suggest that PCMT1 may affect the immune microenvironment of tumors, and inhibition of PCMT1 may better promote anti-tumor immunity (Additional file
3).
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